code: def conformer_rnnt_base() -> RNNT:
      r"""Builds basic version of Conformer RNN-T model.
  
      Returns:
          RNNT:
              Conformer RNN-T model.
      """
      return conformer_rnnt_model(
          input_dim=80,
          encoding_dim=1024,
          time_reduction_stride=4,
          conformer_input_dim=256,
          conformer_ffn_dim=1024,
          conformer_num_layers=16,
          conformer_num_heads=4,
          conformer_depthwise_conv_kernel_size=31,
          conformer_dropout=0.1,
          num_symbols=1024,
          symbol_embedding_dim=256,
          num_lstm_layers=2,
          lstm_hidden_dim=512,
          lstm_layer_norm=True,
          lstm_layer_norm_epsilon=1e-5,
          lstm_dropout=0.3,
          joiner_activation="tanh",
      )
  
imports: import math
  from typing import Dict, List, Optional, Tuple
  import torch
  from torchaudio.models import Conformer, RNNT
  from torchaudio.models.rnnt import _Joiner, _Predictor, _TimeReduction, _Transcriber
label_desc: Use image node_id 2 for calling a global function with example usage: conformer_rnnt_base() and returns: conformer_rnnt_model